AI Terms
Definition: Feature engineering is the process of selecting and transforming features from raw data to improve the performance of machine learning models.
Detailed Description:
Feature engineering is a critical step in the machine learning pipeline. By creating relevant and informative features, you can improve the accuracy and interpretability of your models.
Common feature engineering techniques include:
Feature engineering is often an iterative process that requires domain knowledge and experimentation.
Related Terms:
FAQs:
Why is feature engineering important?
What are some common feature engineering techniques?
How can feature engineering be used to improve model accuracy?
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